Context-specific vocabulary selection for image reporting

ABSTRACT

Methods and systems for using contextual information to generate reports for image studies. One method includes determining contextual information associated with an image study wherein at least one image included in the image study loaded in a reporting application. The method also includes automatically selecting, with an electronic processor, a vocabulary for a natural language processing engine based on the contextual information. In addition, the method includes receiving, from a microphone, audio data and processing the audio data with the natural language processing engine using the vocabulary to generate data for a report for the image study generated using the reporting application.

BACKGROUND

Embodiments of the invention provide methods and systems for usingcontextual information within a reporting software application togenerate a report, such as a structured report, for an image study.

SUMMARY

A reviewing physician (a “reviewer”) generates a report as part of animage study (e.g., a cardiology report, ultrasound report, etc.). Areviewer may dictate the report and a natural language processing enginemay attempt to understand the words and semantics of free speech todetermine discrete data elements for the report. Although this approachis easy to use from the perspective of the reviewer, the resultingreport is unstructured, which makes data mining and other analyticsdifficult. Also, certain clinical areas lexicons contain specific termsand an expected report structure that cannot be created efficientlythrough free speed recognition. Furthermore, some types of reports(e.g., cardiology) are too complex or too lengthy to be properly handledthrough a natural language processing engine.

Alternatively, structured reporting software applications allow areviewer to generate a structured report. For example, a structuredreporting software application may provide a menu of available reportdata elements that a reviewer may select and then populate theapplicable data elements (e.g., provide values for the selected dataelements). The menu of available data elements is commonly structured asa tree structure, where a user may drill-down from a high-level reporttype to specific data elements. Using such a tree structure, however,requires a reviewer to select discrete data elements that are used toform written sentences included in a final report, which involves alarge amount of user interaction with the software application (e.g.,mouse clicks) that may interrupt the reviewer from viewing data (e.g.,images) that he or she is reporting on. However, the resultingstructured report includes discrete data elements that are clearlydefined, which enables powerful analytics.

Embodiments of the invention provide methods and systems for usingcontextual information within a reporting application, such as a medicalsoftware reporting application, to generate a report. For example, onemethod may include automatically selecting a vocabulary for a naturallanguage processing engine based on contextual information available tothe reporting application and using the selected vocabulary to processfree speech (e.g., spoken or written) representing a report or discretedata elements thereof. Another method may include automaticallyselecting one or more discrete data elements for a structured reportbased on contextual information available to the reporting applicationand displaying the selected one or more discrete data elements to areviewer. In some embodiments, the reviewer may select one of thedisplayed data elements for inclusion in a structured report.

For example, one embodiment provides a method of generating reports forimage studies. The method includes determining contextual informationassociated with an image study, at least one image included in the imagestudy loaded within a reporting application and automatically selecting,with an electronic processor, at least one discrete data element for astructured report generated using the reporting application for theimage study based on the contextual information. The method alsoincludes receiving a value for the at least one discrete data elementand adding the value for the at least one discrete data element to thestructured report.

Another embodiment provides a system for generating a structured reportfor data. The system includes an electronic processor configured todetermine contextual information associated with the data, andautomatically select at least one discrete data element for a structuredreport generated using the reporting application for the data based onthe contextual information. The electronic processor is also configuredto receive a value for the at least one discrete data element, and addthe value for the at least one discrete data element to the structuredreport.

An additional embodiment provides non-transitory computer-readablemedium that includes instructions that, when executed by an electronicprocessor, perform a set of functions. The set of functions includesdetermining contextual information associated with at least one imageand automatically selecting at least one discrete data element for astructured report generated using a reporting application for the imagestudy based on the contextual information. The set of functions alsoincludes receiving a value for the at least one discrete data elementand adding the value for the at least one discrete data element to thestructured report within the reporting application.

Yet another embodiment provides a method of generating reports for imagestudies. The method includes determining contextual informationassociated with an image study, wherein at least one image included inthe image study loaded in a reporting application. The method alsoincludes automatically selecting, with an electronic processor, avocabulary for a natural language processing engine based on thecontextual information. In addition, the method includes receiving, froma microphone, audio data and processing the audio data with the naturallanguage processing engine using the vocabulary to generate data for areport for the image study generated using the reporting application.

Another embodiment provides a system for generating a structured reportfor data. The system includes an electronic processor. The electronicprocessor is configured to determine contextual information associatedwith the data, automatically select a vocabulary for a natural languageprocessing engine based on the contextual information, receive audiodata from a microphone, and process the audio data with the naturallanguage processing engine using the vocabulary to generate thestructured report for the data.

A further embodiment provides non-transitory computer-readable mediumincluding instructions that, when executed by an electronic processor,perform a set of functions. The set of functions includes determiningcontextual information associated with at least one image loaded in areporting application and automatically selecting a vocabulary for anatural language processing engine based on the contextual information.The set of functions also includes receiving audio data and processingthe audio data with the natural language processing engine using thevocabulary to generate data for a report for the at least one imagegenerated using the reporting application.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 schematically illustrates a system for generating a report.

FIG. 2 is a flow chart illustrating a method performed using the systemof FIG. 1 to generate for a report based on contextual information.

DETAILED DESCRIPTION

FIG. 1 schematically illustrates a system 10 for generating a report foran image study. It should be understood that FIG. 1 illustrates only oneexample of a system 10 for generating a report and that otherconfigurations are possible. As shown in FIG. 1, the system 10 includesa computing device 12 that includes an electronic processor 14,non-transitory computer-readable media 16, and an input/output interface18. Although the electronic processor 14, the computer-readable media16, and the input/output interface 18 are illustrated as part of asingle computing device 12 (e.g., such as a personal computer or aserver), the components of the computing device 12 may be distributedover multiple computing devices 12. Similarly, the computing device 12may include multiple electronic processors, computer-readable mediamodules, and input/output interfaces and may include additionalcomponents than those illustrated in FIG. 1.

The electronic processor 14 retrieves and executes instructions storedin the computer-readable media 16. The electronic processor 14 may alsostore data to the computer-readable media 16. The computer-readablemedia 16 may include non-transitory computer readable media and mayinclude volatile memory, non-volatile memory, or combinations thereof.In some embodiments, the computer-readable media 16 includes a diskdrive or other type of large capacity storage mechanism.

The input/output interface 18 receives information from sources externalto the computing device 12 and outputs information from the computingdevice 12 to external sources. For example, the input/output interface18 may include a network interface, such as an Ethernet card or awireless network card, that allows the computing device 12 to send andreceive information over a network, such as a local area network or theInternet. In particular, as illustrated in FIG. 1, in some embodiments,the input/output interface 18 communicates with an image database 20 anda report database 22 over a wired or wireless connection or network. Theimage database 20 may store patient information, including images,patient identifiers, patient history, order information, and the like.The report database 22 stores reports, such as structured image studyreports. In some embodiments, the image database 20 and the reportdatabase 22 are combined in a single database. In other embodiments, theimage database 20 and/or the report database 22 are distributed overmultiple databases. Also, in some embodiments, the image database 20and/or the report database 22 is included within the computing device 12(e.g., as part of the computer-readable media 16).

In some embodiments, the computing device 12 may also include one ormore wired or wireless ports and associated drivers to receive and senddata to and from one or more peripheral devices, such as a keyboard, amicrophone, a mouse, a printer, a monitor, etc., communicating with thecomputing device 12.

The instructions stored in the computer-readable media 16 performparticular functionality when executed by the electronic processor 14.For example, as illustrated in FIG. 1, the computer-readable media 16includes a reporting application 30. As described in more detail below,the reporting application 30, when executed by the electronic processor14, generates reports, such as structured reports for medical imagestudies (e.g., cardiology reports, ultrasound reports, and the like).The reporting application 30 may include a software application thatprovides reporting alone or in combination with other functions (e.g., acombined medical software application). For example, the reportingapplication 30 may provide imaging and reporting, viewing and reporting(e.g., pathology viewing and reporting systems or EKG viewing andreporting systems), and the like.

In some embodiments, the computing device 12 is a personal computeroperated by a reviewer to locally store and execute the reportingapplication 30. However, in other embodiments, the computing device 12is a server that hosts the reporting application 30 as a network-basedapplication. Therefore, a reviewer may access the reporting application30 through a communication network, such as the Internet. Accordingly,in some embodiments, a reviewer is not required to have the reportingapplication 30 installed on their workstation or personal computer.Rather, the reviewer may access the reporting application 30 using abrowser application, such as Internet Explorer® or FireFox®.

The reporting application 30 interacts with the image database 20 toaccess images, generates a report based on the images (e.g., based oninput from a reviewer), and stores the generated report to the reportdatabase 22. In some embodiments, the image database 20 and/or thereport database 22 are included in a picture archiving and communicationsystem (“PACS”). Also, in some embodiments, the computing device 12 isincluded in a PACS. In other embodiments, the computing device 12 mayaccess the image database 20, the report database 22, and othercomponents of a PACS through the input/output interface 18.

As noted above, the reporting application 30 allows a reviewer togenerate a report for an image study (e.g., a set of images associatedwith a patient). In some embodiments, the reporting application 30allows a user to dictate a report using free speech, which the reportingapplication 30 translates into text using a natural language processingengine. However, as noted above, this type of report is often difficultto analyze given its unstructured format. Accordingly, alternatively orin addition, the reporting application 30 may allow a user to build areport using discrete data elements that the user selects through a datastructure, such as a tree-structure (e.g., individually or as subsets).This approach results in a structured report but increases the timerequired and interaction required from the reviewer to generate thereport.

Accordingly, to solve these and other problems associated with existingreporting applications, FIG. 2 illustrates a method 40 performed by thesystem 10 for generating a report for an image study based on contextualinformation. The method 40 is described below as being performed by thereporting application 30 (e.g., as executed by the electronic processor14). However, the method 40 or portions thereof may be performed by oneor more separate software applications that interact with the reportingapplication 30 (e.g., as add-on functionality).

As illustrated in FIG. 2, the method 40 includes determining contextualinformation associated with an image study, at least a portion of which(e.g., at least one image) is loaded (e.g., selected, opened, displayed,etc.) within the reporting application 30 (at block 50). The contextualinformation may include information available from one or more imagesincluded in the image study (e.g., obtained from the image database 20),such as an image type (e.g., a computed tomography image, an ultrasoundimage, or the like), a number of images included in the image study, aportion of an image or a particular image within a series of imagescurrently being displayed within the reporting application 30, DigitalImaging and Communications in Medicine (“DICOM”) header information(e.g., gender information, age information, exam information, and thelike), the hanging protocol associated with the image study (i.e., a setof actions used to arrange images for viewing), or a combinationthereof. Similarly, in some embodiments, the contextual informationincludes anatomy information (e.g., an anatomical structure representedin the medical image), which may be pulled from image header informationor may be automatically identified based on one or more images includedin the image study using image analytics.

Alternatively or in addition, the contextual information may includepatient information associated with images being reported on within thereporting application 30. For example, the reporting application 30 maybe configured to use information contained in the displayed images(e.g., a patient identifier included in header information) to access apatient's medical history, which may be stored in the image database 20or a separate database internal or external to the computing device 12.The patient information may include exams and reports related to theimage study, such as electrophysiology reports and vascular reports, andannotations (e.g., notes, measurements, findings, and the like) providedin related exams or previous reports. Similarly, the reportingapplication 30 may be configured to access the order associated with theimages, which may provide information regarding past exams, pastfindings or diagnoses, an anatomical structure, and patient conditions.Similarly, in some embodiments, the contextual information includesinformation obtained from a medical order associated with an imagestudy. The medical order may be captured through a communicationprotocol, such as HL7, and may indicate what a reviewer is supposed tobe reporting on in a study.

Furthermore, in some embodiments, the contextual information may includethe reviewer's current or previous interactions with the reportingapplication 30 for the image study. For example, the contextualinformation may include an annotation (e.g., a measurement) beingcreated by the reviewer on one or more images of the image study, aposition of a cursor within the images, the reviewer's current focus onthe images (e.g., using eye tracking), or a combination thereof.Similarly, the contextual information may include the workflow state ofthe reviewer within the reporting application 30. For example, thecontextual information may include data elements previously selected bythe reviewer (e.g., from a tree-structure of available discrete dataelements or subsets thereof) and/or values previously provided by thereviewer for one or more of these data elements. The contextualinformation may also include information from prior studies. Forexample, if a prior study exists for a patient, the contextualinformation may include one or more data elements included in the reportassociated with the prior study. As described in more detail below, thiscontextual information may be used to include similar data elements inthe report for the new study, data elements associated with sequentialstudies (e.g., tumor progression, location changes, etc.), or acombination thereof. Similarly, a location of a finding documented in aprior study may be used as contextual information that impacts dataelements for the new study.

After determining the contextual information, the reporting application30 uses the contextual information to perform one or more automaticactions. For example, as illustrated in FIG. 2, the reportingapplication 30 may automatically select at least one discrete dataelement for a structured report generated using the reportingapplication 30 for the image study based on the contextual information(at block 52). In particular, as one example, when the reviewer isreviewing an image of a heart, the reporting application 30 may use thecontextual information to identify that a structured report for an imagestudy of a heart typically includes discrete data elements providingfindings for a left ventricle, a right ventricle, and an aorta.Therefore, the reporting application 30 may automatically identify a setof one or more potential discrete data elements for inclusion within thestructured report. It should be understood that the one or moreautomatically-selected discrete data elements may include individualdata elements, sets of related data elements that form a particularsection of a structured report, or a combination thereof.

In some embodiments, the reporting application 30 displays a selecteddiscrete data element to the reviewer and receives a selection from areviewer indicating whether the reviewer wants to add or reject the dataelement (e.g., by receiving one or more selections from the reviewer).For example, in some embodiments, the reporting application 30 may beconfigured to automatically add an automatically selected discrete dataelement to the structured report, which the reviewer may reject (e.g.,individually or as a set). Alternatively, the reporting application 30may be configured to display an automatically selected data element tothe reviewer and only add the data element to the structured report inresponse to the reviewer selecting or approving the data element foraddition to the structured report.

In some embodiments, the reporting application 30 may also automaticallyprioritize the set of automatically selected discrete data elements(e.g., based on a determined probability of the data element beingapplicable based on the contextual information) and display the set ofdiscrete data elements with priority information, such as in aprioritized order (from high priority to lowest priority) or with otherindications designating what data elements are considered more probable(or important) than others. For example, the data elements with higherpriority may be displayed in a particular format, such as color, size,font, etc. or displayed with an icon or other indicator. Also, in someembodiments, the reporting application 30 determines alternative optionsfor discrete data elements (i.e., alternative discrete data elements),which the reporting application 30 may display to the reviewer foroptional selection (e.g., approval or rejection).

In another example, the reporting application 30 may display anautomatically selected discrete data element within a data structure(e.g., a tree structure) of available elements (without requiring thatthe reviewer navigate to the particular data element) and allow thereviewer to select the data element within the data structure or furthernavigate the data structure to select a different data element.Accordingly, in this situation, even if the reporting application 30incorrectly identifies a data element for the structured report based onthe contextual information, the reporting application 30 may eliminateinteractions required by the reviewer to navigate a data structure ofavailable data elements. The reporting application 30 may displayautomatically selected data elements in a different format (e.g., in adifferent color, size, font, format, etc.) than manually-selectable dataelements within the data structure so that the reviewer may distinguishbetween automatically-selected data elements and data elements availablefor manual selection.

After automatically selecting the at least one discrete data element,the reporting application 30 receives a value for the at least onediscrete data element (at block 54). In some embodiments, the reportingapplication 30 prompts the reviewer for a value, and the reviewer mayprovide the value by manually entering a value or selecting a value froma list of available values. Accordingly, the reporting application 30may receive the value through an input mechanism of a user interfacegenerated by the reporting application 30. Alternatively, a reviewer mayprovide the value through audio data (i.e., voice input). In thesesituations, the reporting application 30 may receive the audio datathrough interface with a microphone and use a natural languageprocessing (“NLP”) engine to process the audio data and generatecorresponding text data for the data elements.

Also, in some embodiments, the reporting application 30 may receive thevalue from a piece of software automatically generating the value, or acombination thereof. For example, the reporting application 30 or aseparate software application may be configured to automaticallygenerate a value for a discrete data element (e.g., based on userselections of an image or a portion of an image). In embodiments wherethe value is automatically generated, the value may be displayed to auser to receive a user's approval or rejection.

As illustrated in FIG. 2, after receiving the value, the reportingapplication 30 adds the value for the at least one discrete data elementto the structured report (at block 56). Accordingly, a reviewer may usethe automatically selected data elements to build a structured reportthat satisfies the report requirements and preferences of the reviewerin an efficient manner that improves the performance of the reportingapplication 30.

In some embodiments, the reporting application 30 may also use thecontextual information to automatically select other report parameters,such as annotation tools (e.g., measurement tools), display options,report formats, and the like applied by the reporting application 30.Also, the reporting application 30 may learn from reviewer interactionwith automatically selected data elements to adjust selection criteriato learn specific report sections, reviewer preferences, and, in somesituations, entire reports. For example, the reporting application 30may identify automatically selected data elements that were previously(e.g., more than a predetermined threshold) rejected by one or a groupof reviewers and may not select these data elements for future imagestudies. Similarly, in some situations, the reporting application 30 maybe configured to automatically select an entire report template for animage study. Also, as noted above, information from prior studies (e.g.,associated with the same patient) may be used to set up a framework fora report for a new study and may also be used to automatically identifyrelevant locations or areas within the new study (e.g., locations oftumors reported in previous studies).

In addition, in some embodiments, the reporting application 30 tracksthe usage of particular data elements (e.g., a frequency of use acrossone or multiple reviewers) and uses the frequency of use along with thecontextual information to automatically select data elements or otherreport parameters.

As illustrated in FIG. 2, alternatively or in addition to automaticallyselecting one or more data elements for a structured report, thereporting application 30 may automatically select a vocabulary for anatural language processing engine based on the contextual information(at block 60). The reporting application 30 also receives audio datafrom a reviewer interacting with the reporting application 30 (e.g.,through an interface with a microphone) (at block 62) and processes theaudio data with the natural language processing engine using thevocabulary to generate data for a report for the image study generatedusing the reporting application 30 (at block 64). For example, as notedabove, in some embodiments, a reporting application 30 allows a reviewerto generate a report using free speech or allows a reviewer to providevalues for a structured report using free speech. Accordingly, in thesesituations, the reporting application 30 uses a NLP engine to processaudio data and generate textual report data. However, to provide betterfree speech processing, the reporting application 30 selects aparticular vocabulary (e.g., limits a vocabulary of the NLP engine to arestricted set of terms and/or phrases) based on the contextualinformation. For example, when the contextual information indicates thatthe reviewer is generating a cardiology report, the NLP engine processesreceived audio data using only terms or phrases associated withcardiology. In this way, the NLP engine has a greater chance ofunderstanding the semantics of free speech and identifying theappropriate values for a report.

Thus, embodiments of the invention provide systems and methods for usingcontextual information associated with images being reported on within areporting application to generate a report. In particular, thecontextual information allows a reporting application to narrow thenumber of report options to those that relate to the context of thereport. For example, one method may include automatically selecting avocabulary for a NLP engine based on contextual information availablewithin a reporting application and using the selected vocabulary toprocess free speech representing a report or discrete data elementsthereof. Another method may include automatically selecting one or morediscrete data elements for a structured report based on contextualinformation available within a reporting application and optionallydisplaying the selected one or more discrete data elements to thereviewer for approval prior to adding the data elements to a structurereport. As noted above, these methods may be performed independently orin combination. Also, the methods and systems described above may beused with other types of medical data, such as pathology reporting, EKGreporting, or other types of medical systems that provide datainterpreted as a report. For example, sleep studies that report onbreathing data, heart rates, oxygen saturation levels, leg movementdata, and the like, may be generated using the methods and systemsdescribed above. Also, in some embodiments, the methods and systemsdescribed herein may be used to generated reports associated withnon-medical data, such as geological data, aerial surveillance, and thelike.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium may be a tangible device that mayretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein may bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in computer readable storage medium with therespective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or server. In the later scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider). Insome embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described here in with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, may be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that may directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, may be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

What is claimed is:
 1. A method of generating reports for medical imagestudies, the method comprising: determining contextual informationassociated with a medical image study, the medical image study includinga plurality of images generated as part of an imaging procedure, atleast one image included in the medical image study loaded in areporting application, wherein determining the contextual informationincludes processing the medical image study to determine at least oneselected from a group consisting of a number of images included in themedical image study, header information for the at least one image, anda hanging protocol associated with the medical image study;automatically selecting, with an electronic processor, a vocabulary fora natural language processing engine based on the contextualinformation; receiving, from a microphone, audio data; and processingthe audio data with the natural language processing engine using thevocabulary to generate data for a report for the medical image studygenerated using the reporting application, wherein the data for thereport is displayed within the reporting application.
 2. The method ofclaim 1, further comprising: automatically selecting, with theelectronic processor, one or more discrete data elements included in thereport based on the contextual information; and prompting a reviewer fora value for each of the one or more discrete data elements.
 3. Themethod of claim 2, further comprising prompting the reviewer to acceptor reject each of the one or more discrete data elements.
 4. The methodof claim 1, wherein determining the contextual information furtherincludes automatically identifying an anatomical structure representedin the at least one image and determining the contextual informationbased on the anatomical structure.
 5. The method of claim 1, whereindetermining the contextual information further includes determining atleast one of an annotation created by a reviewer within the reportingapplication for the medical image study and a position of a cursorwithin the reporting application.
 6. The method of claim 1 whereindetermining the contextual information further includes determining acurrent focus of a reviewer within the at least one image displayedwithin the reporting application using eye tracking.
 7. The method ofclaim 1, wherein determining the contextual information further includesaccessing at least one of patient information for a patient associatedwith the medical image study and an order associated with the medicalimage study.
 8. The method of claim 1, wherein determining thecontextual information further includes determining at least one of adiscrete data element previously selected by a reviewer for the reportand a value previously specified by the reviewer for the report.
 9. Themethod of claim 1, wherein processing the audio data with the naturallanguage processing engine using the vocabulary to generate the data forthe report includes processing the audio data to populate a data elementof a structured report.
 10. The method of claim 1, further comprisingautomatically select a report parameter for the report based on thecontextual information, wherein the report parameter includes at leastone selected from a group consisting of an annotation tool, a displayoption, and a report format.
 11. A system for generating a structuredreport for a medical image study, the system comprising: an electronicprocessor configured to: determine contextual information associatedwith the medical image study, the medical image study including aplurality of images generated as part of an imaging procedure data andwherein the contextual information includes at least one selected from agroup consisting of a number of images included in the medical imagestudy, header information for at least one image included in the medicalimage study, and a hanging protocol associated with the medical imagestudy; automatically select a vocabulary for a natural languageprocessing engine based on the contextual information; receive audiodata from a microphone; and process the audio data with the naturallanguage processing engine using the vocabulary to generate thestructured report for the data and display the structured report withina reporting application.
 12. The system of claim 11, wherein thecontextual information further includes an anatomical structurerepresented in the at least one image.
 13. The system of claim 11,wherein the contextual information further includes at least one ofpatient information for a patient associated with the data and an orderassociated with the data.
 14. Non-transitory computer-readable mediumincluding instructions that, when executed by an electronic processor,perform a set of functions, the set of functions comprising: determiningcontextual information associated with at least one image loaded in areporting application, the at least one image included in a medicalimage study including a plurality of images and wherein the contextualinformation includes at least one selected from a group consisting of anumber of images included in the medical image study, header informationfor the at least one image, and a hanging protocol associated with themedical image study; automatically selecting a vocabulary for a naturallanguage processing engine based on the contextual information;receiving audio data; and processing the audio data with the naturallanguage processing engine using the vocabulary to generate data for areport for the at least one image and displaying the data generated forthe report using the reporting application.
 15. The computer-readablemedium of claim 14, wherein the report includes a structured report.